Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River
As a response to climate changes, permafrost has deteriorated and the hydrologic process has undergone significant alterations in high-cold regions. The response mechanism still remains unknown. The characteristic contribution was calculated using the random forest (RF) algorithm, AdaBoost algorithm...
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ftmdpi:oai:mdpi.com:/2073-4441/15/13/2347/ 2023-08-20T04:09:08+02:00 Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River Xinze Han Aili Sun Xue Meng Yongshan Liang Yanqing Shen Yu Bai Boyuan Wang Haojie Meng Ruifei He agris 2023-06-25 application/pdf https://doi.org/10.3390/w15132347 EN eng Multidisciplinary Digital Publishing Institute Water Resources Management, Policy and Governance https://dx.doi.org/10.3390/w15132347 https://creativecommons.org/licenses/by/4.0/ Water; Volume 15; Issue 13; Pages: 2347 permafrost hydrology the headwaters of the yellow river (HWYR) discharge and runoff random forest (RF) support vector machine (SVM) Text 2023 ftmdpi https://doi.org/10.3390/w15132347 2023-08-01T10:36:07Z As a response to climate changes, permafrost has deteriorated and the hydrologic process has undergone significant alterations in high-cold regions. The response mechanism still remains unknown. The characteristic contribution was calculated using the random forest (RF) algorithm, AdaBoost algorithm, and gradient-boosted decision tree (GBDT) algorithm. A comprehensive evaluation model was constructed to evaluate the contribution of climate changes to the headwaters of the Yellow River and the influence of permafrost degradation as well as climate-permafrost cooperation on runoff changes. The selected characteristic vectors were chosen as datasets for the support vector machine (SVM) and RF algorithms. A model was constructed for the prediction of permafrost degradation and runoff changes based on climate data. Results demonstrated that climate variables influencing the mean depth-to-permafrost table (DPT) were ranked according to their contributions: air temperature > evapotranspiration > wind speed > relative humidity (RHU) > sunshine duration > precipitation. The descending rank of climate and permafrost variables according to their contributions to runoff was the following: precipitation > sunshine duration > permafrost coverage > evapotranspiration > relative humidity (RHU) > mean DPT > wind speed > maximum DPT > air temperature. The model demonstrated good prediction results. The outputs can provide scientific references in applications related to water resources and the protection of ecologically vulnerable areas in high-cold regions. Text permafrost MDPI Open Access Publishing Water 15 13 2347 |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
permafrost hydrology the headwaters of the yellow river (HWYR) discharge and runoff random forest (RF) support vector machine (SVM) |
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permafrost hydrology the headwaters of the yellow river (HWYR) discharge and runoff random forest (RF) support vector machine (SVM) Xinze Han Aili Sun Xue Meng Yongshan Liang Yanqing Shen Yu Bai Boyuan Wang Haojie Meng Ruifei He Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
topic_facet |
permafrost hydrology the headwaters of the yellow river (HWYR) discharge and runoff random forest (RF) support vector machine (SVM) |
description |
As a response to climate changes, permafrost has deteriorated and the hydrologic process has undergone significant alterations in high-cold regions. The response mechanism still remains unknown. The characteristic contribution was calculated using the random forest (RF) algorithm, AdaBoost algorithm, and gradient-boosted decision tree (GBDT) algorithm. A comprehensive evaluation model was constructed to evaluate the contribution of climate changes to the headwaters of the Yellow River and the influence of permafrost degradation as well as climate-permafrost cooperation on runoff changes. The selected characteristic vectors were chosen as datasets for the support vector machine (SVM) and RF algorithms. A model was constructed for the prediction of permafrost degradation and runoff changes based on climate data. Results demonstrated that climate variables influencing the mean depth-to-permafrost table (DPT) were ranked according to their contributions: air temperature > evapotranspiration > wind speed > relative humidity (RHU) > sunshine duration > precipitation. The descending rank of climate and permafrost variables according to their contributions to runoff was the following: precipitation > sunshine duration > permafrost coverage > evapotranspiration > relative humidity (RHU) > mean DPT > wind speed > maximum DPT > air temperature. The model demonstrated good prediction results. The outputs can provide scientific references in applications related to water resources and the protection of ecologically vulnerable areas in high-cold regions. |
format |
Text |
author |
Xinze Han Aili Sun Xue Meng Yongshan Liang Yanqing Shen Yu Bai Boyuan Wang Haojie Meng Ruifei He |
author_facet |
Xinze Han Aili Sun Xue Meng Yongshan Liang Yanqing Shen Yu Bai Boyuan Wang Haojie Meng Ruifei He |
author_sort |
Xinze Han |
title |
Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
title_short |
Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
title_full |
Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
title_fullStr |
Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
title_full_unstemmed |
Recognition and Prediction of Collaborative Response Characteristics of Runoff and Permafrost to Climate Changes in the Headwaters of the Yellow River |
title_sort |
recognition and prediction of collaborative response characteristics of runoff and permafrost to climate changes in the headwaters of the yellow river |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/w15132347 |
op_coverage |
agris |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Water; Volume 15; Issue 13; Pages: 2347 |
op_relation |
Water Resources Management, Policy and Governance https://dx.doi.org/10.3390/w15132347 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/w15132347 |
container_title |
Water |
container_volume |
15 |
container_issue |
13 |
container_start_page |
2347 |
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1774721875005407232 |